Genome-wide association studies (GWAS) have been enormously successful over the past 5-10 years in identifying common genetic variants for a wide range of cardiovascular diseases and their risk factors. Yet much of the genetic variation associated with these traits remains unexplained, suggesting that there are still many undiscovered genetic variants to be found. A variety of explanations have been posited to explain the source of this unidentified genetic variation, including gene x environment interaction, gene x gene interaction and additional common variants with smaller effects. One important potential source of this unidentified variation may be less common or rare variants. To pursue such variants, targeted and exome sequencing studies have been conducted over the past few years. The goal of these studies was to fully delineate all genetic variation in targeted or exonic regions and its association with disease traits and risk factors. Whole genome sequencing may be more fruitful in obtaining a full delineation of the genetic variation in the genome and may indeed provide greater success than exome sequencing in locating the causal variants for GWAS signals that are frequently outside protein coding regions. A family study is likely to provide an efficient design to evaluate such variants, since the frequency of a rare variant in families (where these variants are passed down the generations) is substantially larger than the frequency of that variant in the general population. Furthermore, family studies provide an important structure to impute rare variation much more accurately than in populations of unrelated individuals of the same size, thereby saving sequencing costs as fewer individuals need to be sequenced. Thus, we propose the following aims: Aim 1: To use existing GWA, exome chip and whole genome sequencing genotypes in a subset of Framingham Heart Study family participants to impute whole genome sequence variants in remaining family members with GWA and exome chip genotypes. We will examine the added value of using exome chip variants in this imputation. We will explore several approaches for imputation to determine which approach provides the best imputation quality of imputed genotypes. Additionally, we will examine whether other reference backbones for imputation outside the Framingham Study provide better imputation quality than individuals in Framingham with all three types of genetic variants (WGS, exome chip and GWA); and Aim 2: To use the best quality imputed whole genome sequence variation obtained in Aim 1 to examine the associations between less common and rare variants with echocardiographic traits. This research provides the foundation for pursuing whole genome sequencing studies in the Framingham Heart Study and in collaborating family studies.